Call Structural Variants using NAIBR

Call structural variants using NAIBR (plus)

at least 4 cores/threads available
sequence alignments: .bam ❗ coordinate-sorted ❗ phased
genome assembly in FASTA format: .fasta .fa .fasta.gz .fa.gz case insensitive
optional sample grouping file (see below)

This file is optional and only useful if you want variant calling to happen on a per-population level.

takes the format of sample tab group
- spaces can be used as delimeters too
the groups can be numbers or text (i.e. meaningful population names)
you can comment out lines with # for Harpy to ignore them
create with harpy template groupings or manually
if created with harpy template groupings , all the samples will be assigned to group pop1
- make sure to edit the second column to reflect your data correctly.

example file for --populations
sample1 pop1
sample2 pop1
sample3 pop2
sample4 pop1
sample5 pop3
#sample6    pop4

known quirk

There's an unusual error on the Snakemake side of things that happens when the name of a sample and population are identical. It has been unclear how to resolve this issue, so to protect yourself, it's best to make sure the population names are different from the sample names. A simple fix would be to use underscores (_) to differentiate the population name.

After reads have been aligned, e.g. with align bwa , you can use those alignment files (.bam) to call structural variants in your data using NAIBR. While our testing shows that NAIBR tends to find known inversions that LEVIATHAN misses, the program requires phased bam files as input. That means the alignments have a PS or HP tag that indicate which haplotype the read/alignment belongs to. If your alignments don't have phasing tags (none of the current aligners in Harpy do this), then you will need to do a little extra work for NAIBR to work best with your data:

Use the phase snp workflow to phase your SNPs into haplotypes first

Use the resulting phased variants as input into phase bam , where it will phase your alignments, adding the phase tag necessary for NAIBR.

usage
harpy sv naibr OPTIONS... REFERENCE INPUTS...

example
harpy sv naibr --threads 20 genome.fasta Align/bwa

Running Options

In addition to the common runtime options , the sv naibr module is configured using these command-line arguments:

argument	default	description
`INPUTS`		required Files or directories containing phased BAM files
`REFERENCE`		required Reference genome used to generate input alignments
`--contigs`		Contigs to plot in the report
`--extra-params` `-x`		Additional naibr arguments, in quotes
`--min-barcodes` `-b`	`2`	Minimum number of barcode overlaps supporting candidate SV
`--min-quality` `-q`	`30`	Minimum `MQ` (SAM mapping quality) to pass filtering
`--min-size` `-m`	`1000`	Minimum size of SV to detect
`--molecule-distance` `-d`	`100000`	Base-pair distance threshold to separate molecules
`--populations` `-p`		Tab-delimited file of sample<tab>group

Molecule distance

The --molecule-distance option is used to let the program determine how far apart alignments on a contig with the same barcode can be from each other and still considered as originating from the same DNA molecule. See Barcode Thresholds for more information on what this value does. If you want NAIBR to not split molecules in this manner (e.g. you might be looking for inversions greater than this threshold), then set this number to be unreasonably high, such as the length of your largest chromosome.

Single-sample variant calling

When not using a population grouping file via --populations, variants will be called per-sample. Due to the nature of structural variant VCF files, there isn't an entirely fool-proof way of combining the variants of all the samples into a single VCF file, therefore the output will be a VCF for every sample.

Pooled-sample variant calling

With the inclusion of a population grouping file via --populations, Harpy will merge the bam files of all samples within a population and call variants on these alignment pools. Preliminary work shows that this way identifies more variants and with fewer false positives. However, individual-level information gets lost using this approach, so you will only be able to assess group-level variants, if that's what your primary interest is.

NAIBR workflow

Naibr is a variant caller that uses linked read barcode information to call structural variants (indels, inversions, etc.) exclusively, meaning it does not call SNPs. The original Naibr repository has not been updated in a while, so Harpy uses an active fork of it that is available on Bioconda under the name naibr-plus. This fork includes improved accuracy as well as quality-of-life updates.

graph LR
    subgraph id2 ["Population calling"]
        popsplit([merge by population]):::clean
    end
    phased([phased alignments]):::clean-->id2
    popsplit-->A
    phased-->A
    A([index alignments]):::clean --> B([NAIBR]):::clean
    Z([create config file]):::clean --> B
    popsplit --> Z
    phased --> Z
    
    style id2 fill:#f0f0f0,stroke:#e8e8e8,stroke-width:2px,rx:10px,ry:10px
    classDef clean fill:#f5f6f9,stroke:#b7c9ef,stroke-width:2px

The default output directory is SV/naibr with the folder structure below. sample1 and sample2 are generic sample names for demonstration purposes. The resulting folder also includes a workflow directory (not shown) with workflow-relevant runtime files and information.

SV/naibr
├── deletions.bedpe
├── duplications.bedpe
├── inversions.bedpe
├── bedpe
│   ├── sample1.bedpe
│   └── sample2.bedpe
├── configs
│   ├── sample1.config
│   └── sample2.config
├── filtered
│   ├── sample1.fail.bedpe
│   └── sample2.fail.bedpe
├── IGV
│   ├── sample1.reformat.bedpe
│   └── sample2.reformat.bedpe
├── logs
│   ├── sample1.log
│   └── sample2.log
├── reports
│   └── naibr.summary.ipynb
└── vcf
    ├── sample1.vcf
    └── sample2.vcf

item	description
`deletions.bedpe`	an aggregation of all the deletions identified by NAIBR
`duplications.bedpe`	an aggregation of all the duplications identified by NAIBR
`inversions.bedpe`	an aggregation of all the inversions identified by NAIBR
`bedpe/`	structural variants identified by NAIBR
`configs/`	the configuration files harpy generated for each sample
`filtered/`	the variants that failed NAIBR's internal filters
`IGV/`	same as the output `.bedpe` files but in IGV format
`logs/*.log`	what NAIBR writes to `stderr` during operation
`reports/`	summary report with interactive plots of detected SV
`vcf/`	the resulting variants, but in `.VCF` format

By default, Harpy runs naibr with these parameters (excluding inputs and outputs):

min_mapq = 30
min_sv   = 100000
k        = 2
d        = 100000

Below is a list of all naibr runtime options, excluding those Harpy already uses or those made redundant by Harpy's implementation of NAIBR. These are taken directly from the NAIBR documentation. If adding these arguments, do so in quotes:

harpy sv naibr -x "candidates duplications.bedpe" data/alignments/*

NAIBR arguments
-blacklist: BED-file with regions to be excluded from analysis
-candidates: BEDPE-file with novel adjacencies to be scored by NAIBR. This will override automatic detection of candidate novel adjacencies